I recently made a submission to one of Kaggle’s introductory machine learning competitions. The Python code that I wrote was built upon code I wrote for the Coursera Machine Learning by Stanford class in GNU Octave. For the course we put together implementations of common machine learning models, one of those being the logistic regression model I wanted to use for the aforementioned Kaggle competition. I hadn’t written code in Python in a while and felt that porting those models from GNU Octave to Python/Pandas/NumPy would be a great way of getting familiar with the language again. Continue reading “First Experiences with Scikit-Learn”

I use PyCharm for my Python development needs and up until recently I had not been using any sort of version control. I was able to use PyCharm’s provided plugins to connect my project to a remote GitHub repository and felt that others may find a write-up useful for saving time during setup. Continue reading “PyCharm GitHub Integration”

This post is a bit behind schedule but better late than never as they always say. On October 15th I completed the Machine Learning by Stanford University course on Coursera. I had been interested in making a start in machine learning and hoped that the course would provide a good foundation for building upon.